The dual contributions of information instruments in return models: magnitude and direction predictability |
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| Authors: | Bob Korkie Ranjini Sivakumar Harry Turtle |
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| Affiliation: | a Department of Finance and Management Science, School of Business, University of Alberta, Edmonton, Alberta, Canada T6G 2R6;b OPSEU Pension Trust, Toronto, Canada;c Centre for Advanced Studies in Finance, School of Accountancy, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1;d Department of Finance, Insurance and Real Estate, College of Business and Economics, Washington State University, Pullman, WA 99164-4746, USA |
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| Abstract: | By partitioning asset return prediction errors, we show explicitly the dual role of magnitude and sign prediction of return instruments. We demonstrate analytically that sign prediction directly affects heteroskedasticity in asset returns; increases in precision attenuate the heteroskedasticity. Our findings with monthly asset returns are consistent with earlier evidence and indicate that our proposed analytical model captures the sign predictive component of returns. Our results are supportive of a nonlinear return generating model that can be thought of as the product of a model, perhaps linear, for forecasting return signs and a model for forecasting return magnitudes. |
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| Keywords: | Return predictability Magnitude prediction Sign prediction Nonlinearity Heteroskedasticity |
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